A product image that looks real but not quite right.
A headline that sounds convincing until you pause and read it again.<\/p>\n\n\n\n
Most people recognise that moment of hesitation. And often, that\u2019s enough to change behaviour: scrolling past, closing a page, or quietly questioning the brand behind it.<\/p>\n\n\n\n
Now imagine that reaction happening repeatedly, across multiple campaigns and channels.<\/p>\n\n\n\n
For years, digital advertising has prioritised scale and speed producing more content, more quickly. But as generative AI becomes widespread, consumers are starting to ask a more fundamental question: Can this be trusted?<\/p>\n\n\n\n
We are seeing a growing gap between content and trust. According to IAS Consumer Research (2024), 56% of consumers are concerned that AI makes it easier to create misleading content.<\/strong><\/p>\n\n\n\n In a digital environment saturated with AI-generated material, relevance alone is no longer enough. Consumers are increasingly evaluating the credibility, authenticity, and origin of what they see.<\/p>\n\n\n\n For brands, this creates a clear challenge:<\/p>\n\n\n\n Search behaviour is evolving rapidly as AI-powered interfaces become more prominent.<\/p>\n\n\n\n Many industry experts expect traditional click-based traffic to decline over time. At the same time, AI-driven discovery is proving highly valuable: visitors from AI-powered search are, on average, 4.4 times more likely to convert <\/strong>than those from traditional organic search.<\/p>\n\n\n\n As the path from discovery to engagement becomes less predictable, where a brand appears matters just as much as what it says.<\/p>\n\n\n\n Being placed next to low-quality or misleading content can negatively influence perception even if the ad itself is appropriate.<\/p>\n\n\n\n Many existing brand safety strategies were designed for an earlier version of the internet.<\/p>\n\n\n\n Tools such as keyword blocking and static exclusion lists can struggle to identify more subtle risks, particularly content that appears credible on the surface but lacks accuracy or substance.<\/p>\n\n\n\n At the same time, AI is reshaping search itself. IAS AI B2B Study (2025) reports that 61% of media experts believe AI-powered search features will reduce web traffic and clicks.<\/strong><\/p>\n\n\n\n As a result:<\/p>\n\n\n\n There is also growing demand for clearer standards. 68% of media experts believe digital inventory should be labelled<\/strong> – such as \u201chuman-created\u201d or \u201cAI-audited\u201d – by independent third parties.<\/p>\n\n\n\n In complex, AI-driven media environments, the challenge is no longer access to data: it is making confident, informed decisions.<\/p>\n\n\n\n The focus is shifting towards: The objective is not simply more information, but greater confidence and control.<\/p>\n\n\n\n As campaigns become more sophisticated, teams often face information overload, alongside concerns about: At the same time, adoption is accelerating. IAS AI B2B Study (2025) shows that 70% of media experts consider AI a top strategic priority for 2026.<\/strong><\/p>\n\n\n\n However, prioritising AI is not the same as using it effectively.<\/p>\n\n\n\n To succeed, organisations need solutions that:<\/p>\n\n\n\n New approaches, such as the IAS Agent, aim to support faster and more informed decision-making while keeping humans in control.<\/p>\n\n\n\n These tools can help teams to:<\/p>\n\n\n\n This is not about replacing human judgement, but about augmenting it.<\/p>\n\n\n\n \u2e3b<\/p>\n\n\n\n AI-generated content has also contributed to the growth of low-quality environments, including MFA (Made-for-Advertising) sites and cluttered ad placements.<\/p>\n\n\n\n To protect media investment, advertisers can:<\/p>\n\n\n\n Avoid low-quality inventory before bidding<\/p>\n\n\n\n Use pre-bid controls to prevent ads from appearing on identified MFA sites.<\/p>\n\n\n\n Evaluate the impact of ad clutter<\/p>\n\n\n\n Measure whether crowded environments deliver meaningful results\u2014and adjust strategy accordingly.<\/p>\n\n\n\n By combining proactive controls with AI-supported insights, brands can reduce exposure to low-quality environments and focus on placements that drive genuine outcomes.<\/p>\n\n\n\n AI will continue to play a central role in media strategies moving into 2026. But speed and scale are no longer sufficient on their own.<\/p>\n\n\n\n The key principle is simple: automation is most effective when it reinforces authenticity.<\/p>\n\n\n\n Trust is not built through volume. <\/p>\n","protected":false},"excerpt":{"rendered":" When everything can be generated, trust matters more than ever A product image that looks real but not quite right.A headline that sounds convincing until you pause and read it again. Most people recognise that moment of hesitation. And often,…<\/p>\n","protected":false},"author":59,"featured_media":345301,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[295,815,296,757,286,290,283,754,284],"tags":[],"class_list":["post-346507","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ad-fraud-uk","category-articles-uk","category-brand-safety-suitability-uk","category-audio-uk","category-efficiency-optimisation-uk","category-insights-uk","category-programmatic-uk","category-programmatic-uk-2","category-proprietary-platforms-uk"],"acf":[],"yoast_head":"\n\n
\n\n\n\nHow AI is Changing Discovery<\/h4>\n\n\n\n
\n\n\n\nWhy Traditional Brand Safety Approaches Are Being Challenged<\/h4>\n\n\n\n
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\n\n\n\nFrom More Data to Better Decisions<\/h4>\n\n\n\n
<\/p>\n\n\n\n\n
\n\n\n\nManaging Complexity Without Losing Oversight<\/h4>\n\n\n\n
\u2022 Lack of transparency in AI systems
\u2022 Increased brand risk
\u2022 Declining content quality across the open web<\/p>\n\n\n\n\n
\n\n\n\nSupporting Smarter Decisions with AI<\/h4>\n\n\n\n
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Protecting Performance in an AI Content Landscape<\/h4>\n\n\n\n
\n\n\n\nLooking Ahead<\/h4>\n\n\n\n
It is built, step by step, with every impression.<\/p>\n\n\n\n